In this section, we show that the DFPV method yields a consistent estimate of the bridge function.
Our approach differs frm the consistency result of [1]} and Mastouri and Zhu et al. [2]}, which depend on the assumption that the true bridge function lies in a specific functional space (such as an RKHS [2]}) or satisfies certain smoothness properties [1]}.
Since our features are adaptive, however, we instead build our result on a Rademacher complexity argument [5]}, which holds for a wide variety of hypothesis space. Furthermore, we do not assume that our hypothesis space contains the true bridge function, which makes this theory of independent interest.
